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Robustness of the Multiple Correlation Coefficient When Sampling From a Mixture of Two Multivariate Normal Populations

 

作者: Alphonse K. A. Amey,  

 

期刊: Communications in Statistics - Simulation and Computation  （Taylor Available online 1990）
卷期: Volume 19, issue 4  

页码: 1443-1457

 

ISSN:0361-0918

 

年代: 1990

 

DOI:10.1080/03610919008812927

 

出版商: Marcel Dekker, Inc.

 

关键词: Multiple correlation coefficient;mixture of two multivariate normals;linear non-central Wishart density;sample covariance matrix;robustness;significance level

 

数据来源: Taylor

 

摘要:

The density of the multiple correlation coefficient is derived by direct integration when the sample covariance matrix has a linear non-central distribution. Using the density, we deduce the null and non-null distribution of the multiple correlation coefficient when sampling from a mixture of two multivariate normal populations with the same covariance matrix. We also compute actual significance levels of the test of the hypothesis Ho: ρ1·2…p= 0 versus Ha:ρ1·2…p> 0, given the mixture model.

 

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